Matthias Lutz

Background: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain the number one reason for disease and mortality worldwide, cardiology offers potent monitoring use cases with patients in their out-of-hospital daily routines. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. Methods: A literature search was conducted across five databases, and the results were examined according to the study protocols, technical approaches, and qualitative and quantitative parameters measured. Results: Out of 166 articles, 8 studies were included in this systematic review; these cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure, and atrial fibrillation using various app, wearable, and health device combinations. Conclusions: Depending on the researcher’s motivation, a fusion of apps, patient-reported outcome measures, and non-invasive sensors can be orchestrated in a meaningful way, adding major contributions to monitoring concepts for both individual patients and larger cohorts.

(1) Background: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain reason number one for disease and mortality worldwide, cardiology offers potent monitoring use-cases with patients in their out-of-hospital daily routine. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. (2) Methods: A literature search was conducted across five databases and the results were examined according to the study protocols, technical approaches and qualitative and quantitative parameters measured. (3) Results: Out of 166 articles, 8 studies were included in this systematic review. These cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure and atrial fibrillation using various app, wearable and health device combination. (4) Conclusions: Depending on the researcher’s motivation a fusion of apps, patient reported outcome measures and non-invasive sensors can be orchestrated in a meaningful way adding major contributions to monitoring concepts for both, individual patients and larger cohorts.

Zusammenfassung. Das Prinzip der bioresorbierbaren vaskulären Scaffolds ist ein guter Ansatz zur Lösung der residuellen Problematik der perkutanen Koronar-Interventionen, die trotz Einführung und immensen Weiterentwicklungen der Metall-Stents eine kontinuierliche Zunahme von unerwünschten Ereignissen über die Jahre hinweg aufweisen. Als Vorteil können die bioresorbierbaren vaskulären Scaffolds zum einen die Wiederherstellung der physiologischen Gefässeigenschaften gewährleisten; zum anderen fehlt – nach der Resorption – im Unterschied zu permanenten Metall-Implantaten, die Ursache für die Entstehung von In-Stent-Re-Stenosen oder späten Stent-Thrombosen, welche noch immer die grösste Limitation der Metall-Stents darstellen [1]. Zwar konnte der erste richtige Vertreter der bioresorbierbaren vaskulären Scaffolds (Absorb) nach anfänglich guten Ergebnissen, diese im weiteren Verlauf seiner Anwendung nicht bestätigen, sodass er vom Markt genommen wurde. Allerdings konnten aus den Fehler-Analysen wichtige Erkenntnisse gewonnen werden, die die Weiterentwicklung der aktuell zugelassenen Scaffolds beeinflusst haben, sodass inzwischen Scaffolds auf dem Markt sind, die eine mit Metall-Stents vergleichbare Strebendicke aufweisen und dabei gute Studienergebnisse hervorbringen. Auch wenn die Anzahl der behandelten Patienten und die Studien-Qualität noch nicht ausreichen, um die aktuellen europäischen Leitlinien zu ändern, die aktuell nur auf den Absorb-Daten beruhen, so zeigt sich doch eine erfolgsversprechende Datenlage im Vergleich zu 2018, als die Leitlinien verfasst wurden. Die erfolgsversprechenden Studienergebnisse bei der Behandlung von infrapoplitealen Stenosen und die Bereitschaft der Hersteller, an weiteren Produktgenerationen zu arbeiten, zeigen, dass die Therapie mittels bioresorbierbaren vaskulären Scaffolds noch lange nicht am Ende steht, sondern – nach einem holprigen Beginn – sich jetzt am Anfang einer Renaissance befindet.

Coronary heart disease is a common cause of death despite being preventable. To treat the underlying plaque deposits in the arterial walls, intravascular optical coherence tomography can be used by experts to detect and characterize the lesions. In clinical routine, hundreds of images are acquired for each patient which requires automatic plaque detection for fast and accurate decision support. So far, automatic approaches rely on classic machine learning methods and deep learning solutions have rarely been studied. Given the success of deep learning methods with other imaging modalities, a thorough understanding of deep learning-based plaque detection for future clinical decision support systems is required. We address this issue with a new dataset consisting of in-vivo patient images labeled by three trained experts. Using this dataset, we employ state-of-the-art deep learning models that directly learn plaque classification from the images. For improved performance, we study different transfer learning approaches. Furthermore, we investigate the use of cartesian and polar image representations and employ data augmentation techniques tailored to each representation. We fuse both representations in a multi-path architecture for more effective feature exploitation. Last, we address the challenge of plaque differentiation in addition to detection. Overall, we find that our combined model performs best with an accuracy of 91.7%, a sensitivity of 90.9% and a specificity of 92.4%. Our results indicate that building a deep learning-based clinical decision support system for plaque detection is feasible.

Severe aortic stenosis (AS) is a common, serious valve disease in which no effective medical therapy is available and, if not treated by intervention, has a 5-year survival of only 40–60%. Despite the availability of guidelines supporting the effective use of surgical aortic valve replacement (SAVR) or transcatheter aortic valve implantation (TAVI) to treat the majority of these patients, adherence to these guidelines in clinical practice is still unsatisfactory. Several recent studies have emphasised the necessity for improved communication between multidisciplinary teams, with the aim to ensure that severe AS patients receive appropriate treatment. IMPULSE is a prospective, multicentre, European registry designed to gather data over 12 months on the treatment decisions made by referring physicians for patients newly diagnosed with severe AS. Each patient has a follow-up of 3 months. The study will consist of two observational phases to assess the appropriateness and rate of referral based on current guidelines prior to and after an interventional phase aiming to determine whether a simple quality of care intervention improves patient management. Data will be analysed firstly, to determine the appropriateness of treatment decisions for the management of severe AS in current European clinical practice, and secondly, to evaluate the effectiveness of facilitated data relay from a designated echocardiography department nurse to the referring physician early after diagnosis in improving quality of care. Additionally, variables will be identified that are associated with inappropriate decision-making. Collectively, the aim will be to design a clinical pathway that will improve the timely management of patients with newly diagnosed severe AS.

Background: Previous experimental studies concluded that stem cells (SC) may exert their beneficial effects on the ischemic heart by paracrine activation of antiapoptotic pathways. In order to identify potential cardioprotective mediators, we performed a systematic analysis of the differential gene expression of hematopoietic SC after coculture with cardiomyocytes (CM). Methods: After 48 h of coculture with neonatal rat ventricular CM (NRVCM), two consecutive cell sorting steps generated a highly purified population of conditioned murine hematopoietic SC (>99%). Next, a genome-wide microarray analysis of cocultured vs. monocultured hematopoietic SC derived from three independent experiments was performed. The analysis of differentially expressed genes was focused on products that are secretable and/or membrane-bound and potentially involved in antiapoptotic signalling. Results: We found CCL-12, Macrophage Inhibitory Factor, Fibronectin and connexin 40 significantly upregulated in our coculture model. An ELISA of cell culture supernatants was performed to confirm secretion of candidate genes and showed that coculture supernatants revealed markedly higher CCL-12 concentrations. Moreover, we stimulated NRVCM with concentrated coculture supernatants which resulted in a significant reduction of apoptosis compared to monoculture-derived supernatant. Mechanistically, NRVCMs stimulated with coculture supernatants showed a higher level of AKT-phosphorylation, consistent with enhanced antiapoptotic signaling. Conclusion: In summary, our results show that the interaction between hematopoietic SC and NRVCM led to a modified gene expression and induction of antiapoptotic pathways. These findings may thus at least in part explain the cardioprotective effects of hematopoietic SC.